diff --git a/modelforge/tests/test_models.py b/modelforge/tests/test_models.py
index f64cce95..41e406af 100644
--- a/modelforge/tests/test_models.py
+++ b/modelforge/tests/test_models.py
@@ -68,6 +68,7 @@ def test_energy_scaling_and_offset():
 def test_forward_pass(inference_model, batch_QM9_ANI2x):
     # this test sends a single batch from different datasets through the model
 
+    batch = batch_QM9_ANI2x
     nnp_input = batch.nnp_input
     nr_of_mols = nnp_input.atomic_subsystem_indices.unique().shape[0]
 
@@ -82,6 +83,7 @@ def test_calculate_energies_and_forces(inference_model, batch_QM9_ANI2x):
     """
     Test the calculation of energies and forces for a molecule.
     """
+    batch = batch_QM9_ANI2x
     import torch
 
     nnp_input = batch.nnp_input
@@ -319,10 +321,11 @@ def test_pairlist_on_dataset(initialized_dataset):
         assert shapePairlist[0] == 2
 
 
-def test_casting(batch, inference_model):
+def test_casting(batch_QM9_ANI2x, inference_model):
     # test dtype casting
     import torch
 
+    batch = batch_QM9_ANI2x
     batch_ = batch.to(dtype=torch.float64)
     assert batch_.nnp_input.positions.dtype == torch.float64
     batch_ = batch_.to(dtype=torch.float32)
@@ -354,6 +357,7 @@ def test_equivariant_energies_and_forces(
     Test the calculation of energies and forces for a molecule.
     NOTE: test will be adapted once we have a trained model.
     """
+    batch = batch_QM9_ANI2x
     import torch
     from dataclasses import replace